Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.
Abstract: This study demonstrates the use of Class F fly ash in
combination with lime or lime kiln dust in the full depth reclamation
(FDR) of asphalt pavements. FDR, in the context of this paper, is a
process of pulverizing a predetermined amount of flexible pavement
that is structurally deficient, blending it with chemical additives and
water, and compacting it in place to construct a new stabilized base
course. Test sections of two structurally deficient asphalt pavements
were reclaimed using Class F fly ash in combination with lime and
lime kiln dust. In addition, control sections were constructed using
cement, cement and emulsion, lime kiln dust and emulsion, and mill
and fill. The service performance and structural behavior of the FDR
pavement test sections were monitored to determine how the fly ash
sections compared to other more traditional pavement rehabilitation
techniques. Service performance and structural behavior were
determined with the use of sensors embedded in the road and Falling
Weight Deflectometer (FWD) tests. Monitoring results of the FWD
tests conducted up to 2 years after reclamation show that the cement,
fly ash+LKD, and fly ash+lime sections exhibited two year resilient
modulus values comparable to open graded cement stabilized
aggregates (more than 750 ksi). The cement treatment resulted in a
significant increase in resilient modulus within 3 weeks of
construction and beyond this curing time, the stiffness increase was
slow. On the other hand, the fly ash+LKD and fly ash+lime test
sections indicated slower shorter-term increase in stiffness. The fly
ash+LKD and fly ash+lime section average resilient modulus values
at two years after construction were in excess of 800 ksi. Additional
longer-term testing data will be available from ongoing pavement
performance and environmental condition data collection at the two
pavement sites.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.
Abstract: One problem of synthetic sunflower cultivation is an
erratic germination of the seeds. To improve the germination, presowing
seed treatment with an ultrasound was tested. All treatments
were carried out at 40 kHz frequency with the intensities of 40, 60,
80 and 100% of the ultrasonic generator total power (250 W) for the
durations of 5, 10, 15 and 20 minutes. Data on seed germination
percentage, seed vigor index (SVI), root and shoot lengths of
seedlings were collected. The results showed that germination, SVI,
root and shoot lengths of ultrasonic treated seedlings were different
from the control, depending on intensity of the ultrasound. The
effects of ultrasonic treatment were significant on germination,
resulting in a maximum increase of 43% at 40 and 60% intensities
compared to that of the control seeds. In addition, seedlings of these 2
treatments had higher SVI and longer root and shoot lengths than that
of the control seedlings. All treatment durations resulted in higher
germination and SVI, longer root and higher shoot lenghts of
seedlings than the control. Among the duration treatments, only SVI
and seedling root length were significantly different.
Abstract: Many footbridges have natural frequencies that
coincide with the dominant frequencies of the pedestrian-induced
load and therefore they have a potential to suffer excessive vibrations
under dynamic loads induced by pedestrians. Some of the design
standards introduce load models for pedestrian loads applicable for
simple structures. Load modeling for more complex structures, on the
other hand, is most often left to the designer. The main focus of this
paper is on the human induced forces transmitted to a footbridge and
on the ways these loads can be modeled to be used in the dynamic
design of footbridges. Also design criteria and load models proposed
by widely used standards were introduced and a comparison was
made. The dynamic analysis of the suspension bridge in Kolin in the
Czech Republic was performed on detailed FEM model using the
ANSYS program system. An attempt to model the load imposed by a
single person and a crowd of pedestrians resulted in displacements
and accelerations that are compared with serviceability criteria.
Abstract: Sputum smear conversion after one month of antituberculosis
therapy in new smear positive pulmonary tuberculosis
patients (PTB+) is a vital indicator towards treatment success. The
objective of this study is to determine the rate of sputum smear
conversion in new PTB+ patients after one month under treatment of
National Institute of Diseases of the Chest and Hospital (NIDCH).
Analysis of sputum smear conversion was done by re-clinical
examination with sputum smear microscopic test after one month.
Socio-demographic and hematological parameters were evaluated to
perceive the correlation with the disease status. Among all enrolled
patients only 33.33% were available for follow up diagnosis and of
them only 42.86% patients turned to smear negative. Probably this
consequence is due to non-coherence to the proper disease
management. 66.67% and 78.78% patients reported low haemoglobin
and packed cell volume level respectively whereas 80% and 93.33%
patients accounted accelerated platelet count and erythrocyte
sedimentation rate correspondingly.
Abstract: Camera calibration is an indispensable step for augmented
reality or image guided applications where quantitative information
should be derived from the images. Usually, a camera
calibration is obtained by taking images of a special calibration object
and extracting the image coordinates of projected calibration marks
enabling the calculation of the projection from the 3d world coordinates
to the 2d image coordinates. Thus such a procedure exhibits
typical steps, including feature point localization in the acquired
images, camera model fitting, correction of distortion introduced by
the optics and finally an optimization of the model-s parameters. In
this paper we propose to extend this list by further step concerning
the identification of the optimal subset of images yielding the smallest
overall calibration error. For this, we present a Monte Carlo based
algorithm along with a deterministic extension that automatically
determines the images yielding an optimal calibration. Finally, we
present results proving that the calibration can be significantly
improved by automated image selection.
Abstract: Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, many real life optimization problems often
require finding optimal solution to complex high dimensional,
multimodal problems involving computationally very expensive
fitness function evaluations. Use of evolutionary algorithms in such
problem domains is thus practically prohibitive. An attractive
alternative is to build meta models or use an approximation of the
actual fitness functions to be evaluated. These meta models are order
of magnitude cheaper to evaluate compared to the actual function
evaluation. Many regression and interpolation tools are available to
build such meta models. This paper briefly discusses the
architectures and use of such meta-modeling tools in an evolutionary
optimization context. We further present two evolutionary algorithm
frameworks which involve use of meta models for fitness function
evaluation. The first framework, namely the Dynamic Approximate
Fitness based Hybrid EA (DAFHEA) model [14] reduces
computation time by controlled use of meta-models (in this case
approximate model generated by Support Vector Machine
regression) to partially replace the actual function evaluation by
approximate function evaluation. However, the underlying
assumption in DAFHEA is that the training samples for the metamodel
are generated from a single uniform model. This does not take
into account uncertain scenarios involving noisy fitness functions.
The second model, DAFHEA-II, an enhanced version of the original
DAFHEA framework, incorporates a multiple-model based learning
approach for the support vector machine approximator to handle
noisy functions [15]. Empirical results obtained by evaluating the
frameworks using several benchmark functions demonstrate their
efficiency
Abstract: Environmental factors affect agriculture production
productivity and efficiency resulted in changing of profit efficiency.
This paper attempts to estimate the impacts of environmental factors
to profitability of rice farmers in the Red River Delta of Vietnam. The
dataset was extracted from 349 rice farmers using personal
interviews. Both OLS and MLE trans-log profit functions were used
in this study. Five production inputs and four environmental factors
were included in these functions. The estimation of the stochastic
profit frontier with a two-stage approach was used to measure
profitability. The results showed that the profit efficiency was about
75% on the average and environmental factors change profit
efficiency significantly beside farm specific characteristics. Plant
disease, soil fertility, irrigation apply and water pollution were the
four environmental factors cause profit loss in rice production. The
result indicated that farmers should reduce household size, farm
plots, apply row seeding technique and improve environmental
factors to obtain high profit efficiency with special consideration is
given for irrigation water quality improvement.
Abstract: A mobile agent is a software which performs an
action autonomously and independently as a person or an
organizations assistance. Mobile agents are used for searching
information, retrieval information, filtering, intruder recognition in
networks, and so on. One of the important issues of mobile agent is
their security. It must consider different security issues in effective
and secured usage of mobile agent. One of those issues is the
integrity-s protection of mobile agents.
In this paper, the advantages and disadvantages of each method,
after reviewing the existing methods, is examined. Regarding to this
matter that each method has its own advantage or disadvantage, it
seems that by combining these methods, one can reach to a better
method for protecting the integrity of mobile agents. Therefore, this
method is provided in this paper and then is evaluated in terms of
existing method. Finally, this method is simulated and its results are
the sign of improving the possibility of integrity-s protection of
mobile agents.
Abstract: Heat powered solid sorption is a feasible alternative to
electrical vapor compression refrigeration systems. In this paper,
activated carbon (powder type Maxsorb and fiber type ACF-A10)-
CO2 based adsorption cooling cycles are studied using the pressuretemperature-
concentration (P-T-W) diagram. The specific cooling
effect (SCE) and the coefficient of performance (COP) of these two
cooling systems are simulated for the driving heat source
temperatures ranging from 30 ºC to 90 ºC in terms of different
cooling load temperatures with a cooling source temperature of 25
ºC. It is found from the present analysis that Maxsorb-CO2 couple
shows higher cooling capacity and COP. The maximum COPs of
Maxsorb-CO2 and ACF(A10)-CO2 based cooling systems are found
to be 0.15 and 0.083, respectively. The main innovative feature of
this cooling cycle is the ability to utilize low temperature waste heat
or solar energy using CO2 as the refrigerant, which is one of the best
alternative for applications where flammability and toxicity are not
allowed.
Abstract: In this research, an aerobic composting method is
studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator
(CMA) as the activator in the rubber factory waste composting. The
performance of the composting process was monitored as a function
of carbon and organic matter decomposition rate, temperature and
moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted
alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory
waste composted alone, the finished product does not achieve a
standard of fertilizer, especially the C/N ratio.
Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture
content, temperature, and nutrients of the finished products are acceptable for agriculture use.
Abstract: In this article, a method has been offered to classify
normal and defective tiles using wavelet transform and artificial
neural networks. The proposed algorithm calculates max and min
medians as well as the standard deviation and average of detail
images obtained from wavelet filters, then comes by feature vectors
and attempts to classify the given tile using a Perceptron neural
network with a single hidden layer. In this study along with the
proposal of using median of optimum points as the basic feature and
its comparison with the rest of the statistical features in the wavelet
field, the relational advantages of Haar wavelet is investigated. This
method has been experimented on a number of various tile designs
and in average, it has been valid for over 90% of the cases. Amongst
the other advantages, high speed and low calculating load are
prominent.
Abstract: The study explored the question of who am I? As a (re)construction of cultural identity by delving into globalization, communication, and social change in Malta during a historical moment when Malta became a European Union Member State. Three objectives guided this qualitative study. Firstly the study reviewed European Union (EU) policies that regulate broadcasting and their implementation in Member States, whilst meeting the challenges of globalization and new media technology. Secondly the research investigated the changes of the media landscape via organizational structures, programs and television (TV) content. Finally the study explored the impact of these transformations taking place in the way Maltese live as they (re)construct their cultural identity. Despite the choices available to the Maltese audience, old local traditions and new foreign customs coexist as informants continue to (re)construct their cultural identity and define who they are.
Abstract: E-Appointment Scheduling (EAS) has been developed
to handle appointment for UMP students, lecturers in Faculty of
Computer Systems & Software Engineering (FCSSE) and Student
Medical Center. The schedules are based on the timetable and
university activities. Constraints Logic Programming (CLP) has been
implemented to solve the scheduling problems by giving
recommendation to the users in part of determining any available
slots from the lecturers and doctors- timetable. By using this system,
we can avoid wasting time and cost because this application will set
an appointment by auto-generated. In addition, this system can be an
alternative to the lecturers and doctors to make decisions whether to
approve or reject the appointments.
Abstract: This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.
Abstract: Phase-Contrast MR imaging methods are widely used
for measurement of blood flow velocity components. Also there are
some other tools such as CT and Ultrasound for velocity map
detection in intravascular studies. These data are used in deriving
flow characteristics. Some clinical applications are investigated
which use pressure distribution in diagnosis of intravascular disorders
such as vascular stenosis. In this paper an approach to the problem of
measurement of intravascular pressure field by using velocity field
obtained from flow images is proposed. The method presented in this
paper uses an algorithm to calculate nonlinear equations of Navier-
Stokes, assuming blood as an incompressible and Newtonian fluid.
Flow images usually suffer the lack of spatial resolution. Our
attempt is to consider the effect of spatial resolution on the pressure
distribution estimated from this method. In order to achieve this aim,
velocity map of a numerical phantom is derived at six different
spatial resolutions. To determine the effects of vascular stenoses on
pressure distribution, a stenotic phantom geometry is considered. A
comparison between the pressure distribution obtained from the
phantom and the pressure resulted from the algorithm is presented. In
this regard we also compared the effects of collocated and staggered
computational grids on the pressure distribution resulted from this
algorithm.
Abstract: This paper presents a new heuristic algorithm useful
for long-term planning of survivable WDM networks. A multi-period
model is formulated that combines network topology design and
capacity expansion. The ability to determine network expansion
schedules of this type becomes increasingly important to the
telecommunications industry and to its customers. The solution
technique consists of a Genetic Algorithm that allows generating
several network alternatives for each time period simultaneously and
shortest-path techniques to deduce from these alternatives a least-cost
network expansion plan over all time periods. The multi-period
planning approach is illustrated on a realistic network example.
Extensive simulations on a wide range of problem instances are
carried out to assess the cost savings that can be expected by
choosing a multi-period planning approach instead of an iterative
network expansion design method.
Abstract: Speech corpus is one of the major components in a
Speech Processing System where one of the primary requirements
is to recognize an input sample. The quality and details captured
in speech corpus directly affects the precision of recognition. The
current work proposes a platform for speech corpus generation using
an adaptive LMS filter and LPC cepstrum, as a part of an ANN
based Speech Recognition System which is exclusively designed to
recognize isolated numerals of Assamese language- a major language
in the North Eastern part of India. The work focuses on designing an
optimal feature extraction block and a few ANN based cooperative
architectures so that the performance of the Speech Recognition
System can be improved.
Abstract: The paper presents a compressor anti-surge control
system, that results in maximizing compressor throughput with
pressure standard deviation reduction, increased safety margin
between design point and surge limit line and avoiding possible
machine surge. Alternative control strategies are presented.